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M. Desco

As seen in: Nature
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Articles by M. Desco

Automatizing the deep learning pipeline for out-of-distribution lung segmentation

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By A. Gonzalez Gomez, A. Alonso Gómez, Á. Gómez, M. Desco, M. Buccardi, N. Miguel-Ramiro, M. L. Soto-Montenegro, F. F. Stellari, M. Abella
| Nature Verified
Abstract Automatic segmentation of murine lungs is an integral part of the preclinical research pipeline. Being able to quickly and reliably segment the lungs across hundreds of samples is essential for extracting metrics of interest to study certain pathologies. However, the deep learning (DL) approaches proposed in the literature for this task are trained on homogeneous datasets, limiting their generalizability.
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Qualitative disorder measurements from backscattering spectra through an optical fiber

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By A. Beléndez, A. Marcos-Vidal, J. Ripoll, M. Desco
| osapublishing.org
A. L. Robson, P. C. Dastoor, J. Flynn, W. Palmer, A. Martin, D. W. Smith, A. Woldu, and S. Hua, “Advantages and limitations of current imaging techniques for characterizing liposome morphology,” Front. Pharmacol. 9, 1–8 (2018). [Crossref] S. Gladstein, D. Damania, L. M. Almassalha, L. T. Smith, V. Gupta, H. Subramanian, D. K. Rex, H. K. Roy, and V. Backman, “Correlating colorectal cancer risk with field carcinogenesis progression using partial wave spectroscopic microscopy,” Cancer Med. 7(5), 2109–2120 (2018). [Crossref] T.
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